Notes on technology.
Partner at zaka.vc, investing early in health and industrial technologies. Having seen and read a great deal, and understood rather less of it, I am using this page to organise what stayed. Longer pieces at our blog.
The model is not enough. Alphabet spent twelve years proving it.
The question is not whether the frontier labs are serious about biology but whether being serious is enough. Alphabet has run that experiment for twelve years across Calico, Verily and Isomorphic Labs, and came up empty despite capital, patience and a Nobel-winning model. What was missing is what a focused company can own: proprietary biological data and a program someone will see through. Neutrality is now a moat too, since the biggest vendors hold positions in the assets their customers compete over.
The moat decides whether you can play. The asset decides whether you get paid.
Discovery is priced before anyone knows the molecule works. Schrödinger co-discovered the compound Nimbus sold to Takeda for $4 billion and took home $147 million. A data moat tells you nobody can copy you. It says nothing about who pays you, and in target discovery the gap between those two is the whole business.
In AI drug discovery, the model was never the moat
The question is no longer whether AI can design drugs but who keeps an edge once the frontier labs commoditize the model layer. The one test that survives: does a company manufacture biological data nobody else can. Archetype and business-model labels tell you little; data ownership tells you everything.